26 resultados para Sampling schemes
Resumo:
The precise sampling of soil, biological or micro climatic attributes in tropical forests, which are characterized by a high diversity of species and complex spatial variability, is a difficult task. We found few basic studies to guide sampling procedures. The objective of this study was to define a sampling strategy and data analysis for some parameters frequently used in nutrient cycling studies, i. e., litter amount, total nutrient amounts in litter and its composition (Ca, Mg, Κ, Ν and P), and soil attributes at three depths (organic matter, Ρ content, cation exchange capacity and base saturation). A natural remnant forest in the West of São Paulo State (Brazil) was selected as study area and samples were collected in July, 1989. The total amount of litter and its total nutrient amounts had a high spatial independent variance. Conversely, the variance of litter composition was lower and the spatial dependency was peculiar to each nutrient. The sampling strategy for the estimation of litter amounts and the amount of nutrient in litter should be different than the sampling strategy for nutrient composition. For the estimation of litter amounts and the amount of nutrients in litter (related to quantity) a large number of randomly distributed determinations are needed. Otherwise, for the estimation of litter nutrient composition (related to quality) a smaller amount of spatially located samples should be analyzed. The determination of sampling for soil attributes differed according to the depth. Overall, surface samples (0-5 cm) showed high short distance spatial dependent variance, whereas, subsurface samples exhibited spatial dependency in longer distances. Short transects with sampling interval of 5-10 m are recommended for surface sampling. Subsurface samples must also be spatially located, but with transects or grids with longer distances between sampling points over the entire area. Composite soil samples would not provide a complete understanding of the relation between soil properties and surface dynamic processes or landscape aspects. Precise distribution of Ρ was difficult to estimate.
Resumo:
Volumetric soil water content (theta) can be evaluated in the field by direct or indirect methods. Among the direct, the gravimetric method is regarded as highly reliable and thus often preferred. Its main disadvantages are that sampling and laboratory procedures are labor intensive, and that the method is destructive, which makes resampling of a same point impossible. Recently, the time domain reflectometry (TDR) technique has become a widely used indirect, non-destructive method to evaluate theta. In this study, evaluations of the apparent dielectric number of soils (epsilon) and samplings for the gravimetrical determination of the volumetric soil water content (thetaGrav) were carried out at four sites of a Xanthic Ferralsol in Manaus - Brazil. With the obtained epsilon values, theta was estimated using empirical equations (thetaTDR), and compared with thetaGrav derived from disturbed and undisturbed samples. The main objective of this study was the comparison of thetaTDR estimates of horizontally as well as vertically inserted probes with the thetaGrav values determined by disturbed and undisturbed samples. Results showed that thetaTDR estimates of vertically inserted probes and the average of horizontally measured layers were only slightly and insignificantly different. However, significant differences were found between the thetaTDR estimates of different equations and between disturbed and undisturbed samples in the thetaGrav determinations. The use of the theoretical Knight et al. model, which permits an evaluation of the soil volume assessed by TDR probes, is also discussed. It was concluded that the TDR technique, when properly calibrated, permits in situ, nondestructive measurements of q in Xanthic Ferralsols of similar accuracy as the gravimetric method.
Resumo:
The correct use of closed field chambers to determine N2O emissions requires defining the time of day that best represents the daily mean N2O flux. A short-term field experiment was carried out on a Mollisol soil, on which annual crops were grown under no-till management in the Pampa Ondulada of Argentina. The N2O emission rates were measured every 3 h for three consecutive days. Fluxes ranged from 62.58 to 145.99 ∝g N-N2O m-2 h-1 (average of five field chambers) and were negatively related (R² = 0.34, p < 0.01) to topsoil temperature (14 - 20 ºC). N2O emission rates measured between 9:00 and 12:00 am presented a high relationship to daily mean N2O flux (R² = 0.87, p < 0.01), showing that, in the study region, sampling in the mornings is preferable for GHG.
Resumo:
ABSTRACT Understanding the spatial behavior of soil physical properties under no-tillage system (NT) is required for the adoption and maintenance of a sustainable soil management system. The aims of this study were to quantify soil bulk density (BD), porosity in the soil macropore domain (PORp) and in the soil matrix domain (PORm), air capacity in the soil matrix (ACm), field capacity (FC), and soil water storage capacity (FC/TP) in the row (R), interrow (IR), and intermediate position between R and IR (designated IP) in the 0.0-0.10 and 0.10-0.20 m soil layers under NT; and to verify if these soil properties have systematic variation in sampling positions related to rows and interrows of corn. Soil sampling was carried out in transect perpendicular to the corn rows in which 40 sampling points were selected at each position (R, IR, IP) and in each soil layer, obtaining undisturbed samples to determine the aforementioned soil physical properties. The influence of sampling position on systematic variation of soil physical properties was evaluated by spectral analysis. In the 0.0-0.1 m layer, tilling the crop rows at the time of planting led to differences in BD, PORp, ACm, FC and FC/TP only in the R position. In the R position, the FC/TP ratio was considered close to ideal (0.66), indicating good water and air availability at this sampling position. The R position also showed BD values lower than the critical bulk density that restricts root growth, suggesting good soil physical conditions for seed germination and plant establishment. Spectral analysis indicated that there was systematic variation in soil physical properties evaluated in the 0.0-0.1 m layer, except for PORm. These results indicated that the soil physical properties evaluated in the 0.0-0.1 m layer were associated with soil position in the rows and interrows of corn. Thus, proper assessment of soil physical properties under NT must take into consideration the sampling positions and previous location of crop rows and interrows.
Resumo:
The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.
Resumo:
This study was carried to evaluate the efficiency of the Bitterlich method in growth and yield modeling of the even-aged Eucalyptus stands. 25 plots were setup in Eucalyptus grandis cropped under a high bole system in the Central Western Region of Minas Gerais, Brazil. The sampling points were setup in the center of each plot. The data of four annual mesurements were colleted and used to adjust the three model types using the age, the site index and the basal area as independent variables. The growths models were fitted for volume and mass of trees. The efficiency of the Bitterlich method was confirmed for generating the data for growth and yield modeling.
Resumo:
In order to verify Point-Centered Quarter Method (PCQM) accuracy and efficiency, using different numbers of individuals by per sampled area, in 28 quarter points in an Araucaria forest, southern Paraná, Brazil. Three variations of the PCQM were used for comparison associated to the number of sampled individual trees: standard PCQM (SD-PCQM), with four sampled individuals by point (one in each quarter), second measured (VAR1-PCQM), with eight sampled individuals by point (two in each quarter), and third measuring (VAR2-PCQM), with 16 sampled individuals by points (four in each quarter). Thirty-one species of trees were recorded by the SD-PCQM method, 48 by VAR1-PCQM and 60 by VAR2-PCQM. The level of exhaustiveness of the vegetation census and diversity index showed an increasing number of individuals considered by quadrant, indicating that VAR2-PCQM was the most accurate and efficient method when compared with VAR1-PCQM and SD-PCQM.
Resumo:
Taking into account that the sampling intensity of soil attributes is a determining factor for applying of concepts of precision agriculture, this study aims to determine the spatial distribution pattern of soil attributes and corn yield at four soil sampling intensities and verify how sampling intensity affects cause-effect relationship between soil attributes and corn yield. A 100-referenced point sample grid was imposed on the experimental site. Thus, each sampling cell encompassed an area of 45 m² and was composed of five 10-m long crop rows, where referenced points were considered the center of the cell. Samples were taken from at 0 to 0.1 m and 0.1 to 0.2 m depths. Soil chemical attributes and clay content were evaluated. Sampling intensities were established by initial 100-point sampling, resulting data sets of 100; 75; 50 and 25 points. The data were submitted to descriptive statistical and geostatistics analyses. The best sampling intensity to know the spatial distribution pattern was dependent on the soil attribute being studied. The attributes P and K+ content showed higher spatial variability; while the clay content, Ca2+, Mg2+ and base saturation values (V) showed lesser spatial variability. The spatial distribution pattern of clay content and V at the 100-point sampling were the ones which best explained the spatial distribution pattern of corn yield.
Resumo:
The aim of this study was to compare two methods of tear sampling for protein quantification. Tear samples were collected from 29 healthy dogs (58 eyes) using Schirmer tear test (STT) strip and microcapillary tubes. The samples were frozen at -80ºC and analyzed by the Bradford method. Results were analyzed by Student's t test. The average protein concentration and standard deviation from tears collected with microcapillary tube were 4.45mg/mL ±0.35 and 4,52mg/mL ±0.29 for right and left eyes respectively. The average protein concentration and standard deviation from tears collected with Schirmer Tear Test (STT) strip were and 54.5mg/mL ±0.63 and 54.15mg/mL ±0.65 to right and left eyes respectively. Statistically significant differences (p<0.001) were found between the methods. In the conditions in which this study was conducted, the average protein concentration obtained with the Bradford test from tear samples obtained by Schirmer Tear Test (STT) strip showed values higher than those obtained with microcapillary tube. It is important that concentration of tear protein pattern values should be analyzed according the method used to collect tear samples.
Resumo:
Bioanalytical data from a bioequivalence study were used to develop limited-sampling strategy (LSS) models for estimating the area under the plasma concentration versus time curve (AUC) and the peak plasma concentration (Cmax) of 4-methylaminoantipyrine (MAA), an active metabolite of dipyrone. Twelve healthy adult male volunteers received single 600 mg oral doses of dipyrone in two formulations at a 7-day interval in a randomized, crossover protocol. Plasma concentrations of MAA (N = 336), measured by HPLC, were used to develop LSS models. Linear regression analysis and a "jack-knife" validation procedure revealed that the AUC0-¥ and the Cmax of MAA can be accurately predicted (R²>0.95, bias <1.5%, precision between 3.1 and 8.3%) by LSS models based on two sampling times. Validation tests indicate that the most informative 2-point LSS models developed for one formulation provide good estimates (R²>0.85) of the AUC0-¥ or Cmax for the other formulation. LSS models based on three sampling points (1.5, 4 and 24 h), but using different coefficients for AUC0-¥ and Cmax, predicted the individual values of both parameters for the enrolled volunteers (R²>0.88, bias = -0.65 and -0.37%, precision = 4.3 and 7.4%) as well as for plasma concentration data sets generated by simulation (R²>0.88, bias = -1.9 and 8.5%, precision = 5.2 and 8.7%). Bioequivalence assessment of the dipyrone formulations based on the 90% confidence interval of log-transformed AUC0-¥ and Cmax provided similar results when either the best-estimated or the LSS-derived metrics were used.
Resumo:
"La Niora" is a red pepper variety cultivated in Tadla Region (Morocco) which is used for manufacturing paprika after sun drying. The paprika quality (nutritional, chemical and microbiological) was evaluated immediately after milling, from September to December. Sampling time mainly affected paprika color and the total capsaicinoid and vitamin C contents. The commercial quality was acceptable and no aflatoxins were found, but the microbial load sometimes exceeded permitted levels.